Paper by Martin J. Williams: “With the growing number of rigorous impact evaluations worldwide, the question of how best to apply this evidence to policymaking processes has arguably become the main challenge for evidence-based policymaking. How can policymakers predict whether a policy will have the same impact in their context as it did elsewhere, and how should this influence the design and implementation of policy? This paper introduces a simple and flexible framework to address these questions of external validity and policy adaptation. I show that failures of external validity arise from an interaction between a policy’s theory of change and a dimension of the context in which it is being implemented, and develop a method of “mechanism mapping” that maps a policy’s theory of change against salient contextual assumptions to identify external validity problems and suggest appropriate policy adaptations. In deciding whether and how to adapt a policy in a new context, I show there is a fundamental informational trade-o↵ between the strength and relevance of evidence on the policy from other contexts and the policymaker’s knowledge of the local context. This trade-o↵ can guide policymakers’ judgments about whether policies should be copied exactly from elsewhere, adapted, or invented anew….(More)”
Public Brainpower: Civil Society and Natural Resource Management
Book edited by Indra Øverland: ” …examines how civil society, public debate and freedom of speech affect natural resource governance. Drawing on the theories of Robert Dahl, Jurgen Habermas and Robert Putnam, the book introduces the concept of ‘public brainpower’, proposing that good institutions require: fertile public debate involving many and varied contributors to provide a broad base for conceiving new institutions; checks and balances on existing institutions; and the continuous dynamic evolution of institutions as the needs of society change.
The book explores the strength of these ideas through case studies of 18 oil and gas-producing countries: Algeria, Angola, Azerbaijan, Canada, Colombia, Egypt, Iraq, Kazakhstan, Libya, Netherlands, Nigeria, Norway, Qatar, Russia, Saudi, UAE, UK and Venezuela. The concluding chapter includes 10 tenets on how states can maximize their public brainpower, and a ranking of 33 resource-rich countries and the degree to which they succeed in doing so.
The Introduction and the chapters ‘Norway: Public Debate and the Management of Petroleum Resources and Revenues’, ‘Kazakhstan: Civil Society and Natural-Resource Policy in Kazakhstan’, and ‘Russia: Public Debate and the Petroleum Sector’ of this book are available open access under a CC BY 4.0 license at link.springer.com….(More)”.
Smart contracts: terminology, technical limitations and real world complexity
Eliza Mik at Law, Innovation and Technology: “If one is to believe the popular press and many “technical writings,” blockchains create not only a perfect transactional environment but also obviate the need for banks, lawyers and courts. The latter will soon be replaced by smart contracts: unbiased and infallible computer programs that form, perform and enforce agreements. Predictions of future revolutions must, however, be distinguished from the harsh reality of the commercial marketplace and the technical limitations of blockchains. The fact that a technological solution is innovative and elegant need not imply that it is commercially useful or legally viable. Apart from attempting a terminological “clean-up” surrounding the term smart contract, this paper presents some technological and legal constraints on their use. It confronts the popular claims concerning their ability to automate transactions and to ensure perfect performance. It also examines the possibility of reducing contractual relationships to code and the ability to integrate smart contracts with the complexities of the real world. A closer analysis reveals that smart contracts can hardly be regarded as a semi-mythical technology liberating the contracting parties from the shackles of traditional legal and financial institutions….(More)”.
Governance Reforms: the Good, the Bad, and the Ugly; and the Sound: Examining the Past and Exploring the Future of Public Organizations
This paper addresses governance reforms of the last three and a half decades and looks into the future. This is done in three parts. The first part presents a birds-eye view of the massive literature on governance and governance reforms with a focus on the good, the bad, and ugly sides, then in part two argues for an alternative concept or theory of “sound governance” with characteristics and dimensions that overcome the deficiencies of other models of governance. As a consequence of reforms, the third part examines the past and explores the future of public organizations via “going home” as a conclusion with possible scenarios, challenges, and opportunities….(More)”
Open data is shaking up civic life in eastern Europe
Anna Sienicka in the Financial Times: “I often imagine how different the world would look if citizens and social activists were able to fully understand and use data, and new technologies. Unfortunately, the entry point to this world is often inaccessible for most civil society groups…
The concept of open data has revolutionised thinking about citizens’ participation in civic life. Since the fall of communism, citizens across central and eastern Europe have been fighting for more transparent and responsive governments, and to improve collaboration between civil society and the public sector. When an institution makes its data public, it is a sign that it is committed to being transparent and accountable. A few cities have opened up data about budget spending, for example, but these remain the exception rather than the rule. Open data provides citizens with a tool to directly engage in civic life. For example, they can analyse public expenses to check how their taxes are used, track their MP’s votes or monitor the legislative process….
One of the successful projects in Ukraine is the Open School app, which provides reviews and ratings of secondary schools based on indicators such as the number of pupils who go on to university, school subject specialisations and accessibility. It allows students and parents to make informed decisions about their educational path… Another example comes from the Serbian city of Pancevo, where a maths teacher and a tax inspector have worked together to help people navigate the tax system. The idea is simple: the more people know about taxes, the less likely they are to unconsciously violate the law. Open Taxes is a free, web-based, interactive guide to key national and local taxes…(More)”
Our laws don’t do enough to protect our health data
A particularly sensitive type of big data is medical big data. Medical big data can consist of electronic health records, insurance claims, information entered by patients into websites such as PatientsLikeMeand more. Health information can even be gleaned from web searches, Facebook and your recent purchases.
Such data can be used for beneficial purposes by medical researchers, public health authorities, and healthcare administrators. For example, they can use it to study medical treatments, combat epidemics and reduce costs. But others who can obtain medical big data may have more selfish agendas.
I am a professor of law and bioethics who has researched big data extensively. Last year, I published a book entitled Electronic Health Records and Medical Big Data: Law and Policy.
I have become increasingly concerned about how medical big data might be used and who could use it. Our laws currently don’t do enough to prevent harm associated with big data.
What your data says about you
Personal health information could be of interest to many, including employers, financial institutions, marketers and educational institutions. Such entities may wish to exploit it for decision-making purposes.
For example, employers presumably prefer healthy employees who are productive, take few sick days and have low medical costs. However, there are laws that prohibit employers from discriminating against workers because of their health conditions. These laws are the Americans with Disabilities Act (ADA) and the Genetic Information Nondiscrimination Act. So, employers are not permitted to reject qualified applicants simply because they have diabetes, depression or a genetic abnormality.
However, the same is not true for most predictive information regarding possible future ailments. Nothing prevents employers from rejecting or firing healthy workers out of the concern that they will later develop an impairment or disability, unless that concern is based on genetic information.
What non-genetic data can provide evidence regarding future health problems? Smoking status, eating preferences, exercise habits, weight and exposure to toxins are all informative. Scientists believe that biomarkers in your blood and other health details can predict cognitive decline, depression and diabetes.
Even bicycle purchases, credit scores and voting in midterm elections can be indicators of your health status.
Gathering data
How might employers obtain predictive data? An easy source is social media, where many individuals publicly post very private information. Through social media, your employer might learn that you smoke, hate to exercise or have high cholesterol.
Another potential source is wellness programs. These programs seek to improve workers’ health through incentives to exercise, stop smoking, manage diabetes, obtain health screenings and so on. While many wellness programs are run by third party vendors that promise confidentiality, that is not always the case.
In addition, employers may be able to purchase information from data brokers that collect, compile and sell personal information. Data brokers mine sources such as social media, personal websites, U.S. Census records, state hospital records, retailers’ purchasing records, real property records, insurance claims and more. Two well-known data brokers are Spokeo and Acxiom.
Some of the data employers can obtain identify individuals by name. But even information that does not provide obvious identifying details can be valuable. Wellness program vendors, for example, might provide employers with summary data about their workforce but strip away particulars such as names and birthdates. Nevertheless, de-identified information can sometimes be re-identified by experts. Data miners can match information to data that is publicly available….(More)”.
How people update beliefs about climate change: good news and bad news
Paper by Cass R. Sunstein, Sebastian Bobadilla-Suarez, Stephanie C. Lazzaro & Tali Sharot: “People are frequently exposed to competing evidence about climate change. We examined how new information alters people’s beliefs. We find that people who are not sure that man-made climate change is occurring, and who do not favor an international agreement to reduce greenhouse gas emissions, show a form of asymmetrical updating: They change their beliefs in response to unexpected good news (suggesting that average temperature rise is likely to be less than previously thought) and fail to change their beliefs in response to unexpected bad news (suggesting that average temperature rise is likely to be greater than previously thought). By contrast, people who strongly believe that manmade climate change is occurring, and who favor an international agreement, show the opposite asymmetry: They change their beliefs far more in response to unexpected bad news (suggesting that average temperature rise is likely to be greater than previously thought) than in response to unexpected good news (suggesting that average temperature rise is likely to be smaller than previously thought). The results suggest that exposure to varied scientific evidence about climate change may increase polarization within a population due to asymmetrical updating. We explore the implications of our findings for how people will update their beliefs upon receiving new evidence about climate change, and also for other beliefs relevant to politics and law….(More)”.
The Challenges of Prediction: Lessons from Criminal Justice
Paper by David G. Robinson: “Government authorities at all levels increasingly rely on automated predictions, grounded in statistical patterns, to shape people’s lives. Software that wields government power deserves special attention, particularly when it uses historical data to decide automatically what ought to happen next.
In this article, I draw examples primarily from the domain of criminal justice — and in particular, the intersection of civil rights and criminal justice — to illustrate three structural challenges that can arise whenever law or public policy contemplates adopting predictive analytics as a tool:
1) What matters versus what the data measure;
2) Current goals versus historical patterns; and
3) Public authority versus private expertise.
After explaining each of these challenges and illustrating each with concrete examples, I describe feasible ways to avoid these problems and to do prediction more successfully…(More)”
Tech’s fight for the upper hand on open data
Rana Foroohar at the Financial Times: “One thing that’s becoming very clear to me as I report on the digital economy is that a rethink of the legal framework in which business has been conducted for many decades is going to be required. Many of the key laws that govern digital commerce (which, increasingly, is most commerce) were crafted in the 1980s or 1990s, when the internet was an entirely different place. Consider, for example, the US Computer Fraud and Abuse Act.
This 1986 law made it a federal crime to engage in “unauthorised access” to a computer connected to the internet. It was designed to prevent hackers from breaking into government or corporate systems. …While few hackers seem to have been deterred by it, the law is being used in turf battles between companies looking to monetise the most valuable commodity on the planet — your personal data. Case in point: LinkedIn vs HiQ, which may well become a groundbreaker in Silicon Valley.
LinkedIn is the dominant professional networking platform, a Facebook for corporate types. HiQ is a “data-scraping” company, one that accesses publicly available data from LinkedIn profiles and then mixes it up in its own quantitative black box to create two products — Keeper, which tells employers which of their employees are at greatest risk of being recruited away, and Skill Mapper, which provides a summary of the skills possessed by individual workers. LinkedIn allowed HiQ to do this for five years, before developing a very similar product to Skill Mapper, at which point LinkedIn sent the company a “cease and desist” letter, and threatened to invoke the CFAA if HiQ did not stop tapping its user data.
..Meanwhile, a case that might have been significant mainly to digital insiders is being given a huge publicity boost by Harvard professor Laurence Tribe, the country’s pre-eminent constitutional law scholar. He has joined the HiQ defence team because, as he told me, he believes the case is “tremendously important”, not only in terms of setting competitive rules for the digital economy, but in the realm of free speech. According to Prof Tribe, if you accept that the internet is the new town square, and “data is a central type of capital”, then it must be freely available to everyone — and LinkedIn, as a private company, cannot suddenly decide that publicly accessible, Google-searchable data is their private property….(More)”.
Collaborative Platforms as a Governance Strategy
and Collaborative-Platforms-as-a-Governance-Strategy?redirectedFrom=fulltextCollaborative governance is increasingly viewed as a proactive policy instrument, one in which the strategy of collaboration can be deployed on a larger scale and extended from one local context to another. This article suggests that the concept of collaborative platforms provides useful insights into this strategy of treating collaborative governance as a generic policy instrument. Building on an organization-theoretic approach, collaborative platforms are defined as organizations or programs with dedicated competences and resources for facilitating the creation, adaptation and success of multiple or ongoing collaborative projects or networks. Working between the theoretical literature on platforms and empirical cases of collaborative platforms, the article finds that strategic intermediation and design rules are important for encouraging the positive feedback effects that help collaborative platforms adapt and succeed. Collaborative platforms often promote the scaling-up of collaborative governance by creating modular collaborative units—a strategy of collaborative franchising….(More)”.